Cancers (Jun 2020)
Pilot Multi-Omic Analysis of Human Bile from Benign and Malignant Biliary Strictures: A Machine-Learning Approach
- Jesús M. Urman,
- José M. Herranz,
- Iker Uriarte,
- María Rullán,
- Daniel Oyón,
- Belén González,
- Ignacio Fernandez-Urién,
- Juan Carrascosa,
- Federico Bolado,
- Lucía Zabalza,
- María Arechederra,
- Gloria Alvarez-Sola,
- Leticia Colyn,
- María U. Latasa,
- Leonor Puchades-Carrasco,
- Antonio Pineda-Lucena,
- María J. Iraburu,
- Marta Iruarrizaga-Lejarreta,
- Cristina Alonso,
- Bruno Sangro,
- Ana Purroy,
- Isabel Gil,
- Lorena Carmona,
- Francisco Javier Cubero,
- María L. Martínez-Chantar,
- Jesús M. Banales,
- Marta R. Romero,
- Rocio I.R. Macias,
- Maria J. Monte,
- Jose J. G. Marín,
- Juan J. Vila,
- Fernando J. Corrales,
- Carmen Berasain,
- Maite G. Fernández-Barrena,
- Matías A. Avila
Affiliations
- Jesús M. Urman
- Department of Gastroenterology and Hepatology, Navarra University Hospital Complex, 31008 Pamplona, Spain
- José M. Herranz
- National Institute for the Study of Liver and Gastrointestinal Diseases, CIBERehd, Carlos III Health Institute, 28029 Madrid, Spain
- Iker Uriarte
- National Institute for the Study of Liver and Gastrointestinal Diseases, CIBERehd, Carlos III Health Institute, 28029 Madrid, Spain
- María Rullán
- Department of Gastroenterology and Hepatology, Navarra University Hospital Complex, 31008 Pamplona, Spain
- Daniel Oyón
- Department of Gastroenterology and Hepatology, Navarra University Hospital Complex, 31008 Pamplona, Spain
- Belén González
- Department of Gastroenterology and Hepatology, Navarra University Hospital Complex, 31008 Pamplona, Spain
- Ignacio Fernandez-Urién
- Department of Gastroenterology and Hepatology, Navarra University Hospital Complex, 31008 Pamplona, Spain
- Juan Carrascosa
- Department of Gastroenterology and Hepatology, Navarra University Hospital Complex, 31008 Pamplona, Spain
- Federico Bolado
- Department of Gastroenterology and Hepatology, Navarra University Hospital Complex, 31008 Pamplona, Spain
- Lucía Zabalza
- Department of Gastroenterology and Hepatology, Navarra University Hospital Complex, 31008 Pamplona, Spain
- María Arechederra
- IdiSNA, Navarra Institute for Health Research, 31008 Pamplona, Spain
- Gloria Alvarez-Sola
- National Institute for the Study of Liver and Gastrointestinal Diseases, CIBERehd, Carlos III Health Institute, 28029 Madrid, Spain
- Leticia Colyn
- Program of Hepatology, Center for Applied Medical Research (CIMA), University of Navarra, 31008 Pamplona, Spain
- María U. Latasa
- Program of Hepatology, Center for Applied Medical Research (CIMA), University of Navarra, 31008 Pamplona, Spain
- Leonor Puchades-Carrasco
- Drug Discovery Unit, Instituto de Investigación Sanitaria La Fe, Hospital Universitario y Politécnico La Fe, 46026 Valencia, Spain
- Antonio Pineda-Lucena
- Drug Discovery Unit, Instituto de Investigación Sanitaria La Fe, Hospital Universitario y Politécnico La Fe, 46026 Valencia, Spain
- María J. Iraburu
- Department of Biochemistry and Genetics, School of Sciences; University of Navarra, 31008 Pamplona, Spain
- Marta Iruarrizaga-Lejarreta
- OWL Metabolomics, Bizkaia Technology Park, 48160 Derio, Spain
- Cristina Alonso
- OWL Metabolomics, Bizkaia Technology Park, 48160 Derio, Spain
- Bruno Sangro
- IdiSNA, Navarra Institute for Health Research, 31008 Pamplona, Spain
- Ana Purroy
- IdiSNA, Navarra Institute for Health Research, 31008 Pamplona, Spain
- Isabel Gil
- IdiSNA, Navarra Institute for Health Research, 31008 Pamplona, Spain
- Lorena Carmona
- Proteomics Unit, Centro Nacional de Biotecnología (CNB) Consejo Superior de Investigaciones Científicas (CSIC), 28049 Madrid, Spain
- Francisco Javier Cubero
- Department of Immunology, Ophtalmology & Ear, Nose and Throat (ENT), Complutense University School of Medicine and 12 de Octubre Health Research Institute (Imas12), 28040 Madrid, Spain
- María L. Martínez-Chantar
- National Institute for the Study of Liver and Gastrointestinal Diseases, CIBERehd, Carlos III Health Institute, 28029 Madrid, Spain
- Jesús M. Banales
- National Institute for the Study of Liver and Gastrointestinal Diseases, CIBERehd, Carlos III Health Institute, 28029 Madrid, Spain
- Marta R. Romero
- National Institute for the Study of Liver and Gastrointestinal Diseases, CIBERehd, Carlos III Health Institute, 28029 Madrid, Spain
- Rocio I.R. Macias
- National Institute for the Study of Liver and Gastrointestinal Diseases, CIBERehd, Carlos III Health Institute, 28029 Madrid, Spain
- Maria J. Monte
- National Institute for the Study of Liver and Gastrointestinal Diseases, CIBERehd, Carlos III Health Institute, 28029 Madrid, Spain
- Jose J. G. Marín
- National Institute for the Study of Liver and Gastrointestinal Diseases, CIBERehd, Carlos III Health Institute, 28029 Madrid, Spain
- Juan J. Vila
- Department of Gastroenterology and Hepatology, Navarra University Hospital Complex, 31008 Pamplona, Spain
- Fernando J. Corrales
- National Institute for the Study of Liver and Gastrointestinal Diseases, CIBERehd, Carlos III Health Institute, 28029 Madrid, Spain
- Carmen Berasain
- IdiSNA, Navarra Institute for Health Research, 31008 Pamplona, Spain
- Maite G. Fernández-Barrena
- IdiSNA, Navarra Institute for Health Research, 31008 Pamplona, Spain
- Matías A. Avila
- IdiSNA, Navarra Institute for Health Research, 31008 Pamplona, Spain
- DOI
- https://doi.org/10.3390/cancers12061644
- Journal volume & issue
-
Vol. 12,
no. 6
p. 1644
Abstract
Cholangiocarcinoma (CCA) and pancreatic adenocarcinoma (PDAC) may lead to the development of extrahepatic obstructive cholestasis. However, biliary stenoses can also be caused by benign conditions, and the identification of their etiology still remains a clinical challenge. We performed metabolomic and proteomic analyses of bile from patients with benign (n = 36) and malignant conditions, CCA (n = 36) or PDAC (n = 57), undergoing endoscopic retrograde cholangiopancreatography with the aim of characterizing bile composition in biliopancreatic disease and identifying biomarkers for the differential diagnosis of biliary strictures. Comprehensive analyses of lipids, bile acids and small molecules were carried out using mass spectrometry (MS) and nuclear magnetic resonance spectroscopy (1H-NMR) in all patients. MS analysis of bile proteome was performed in five patients per group. We implemented artificial intelligence tools for the selection of biomarkers and algorithms with predictive capacity. Our machine-learning pipeline included the generation of synthetic data with properties of real data, the selection of potential biomarkers (metabolites or proteins) and their analysis with neural networks (NN). Selected biomarkers were then validated with real data. We identified panels of lipids (n = 10) and proteins (n = 5) that when analyzed with NN algorithms discriminated between patients with and without cancer with an unprecedented accuracy.
Keywords